We present a catalog of quasars with their corresponding redshifts derived from the photometric Kilo-Degree Survey (KiDS) Data Release 4. We achieved it by training machine learning (ML) models, ...using optical
u
g
ri
and near-infrared
Z
Y
J
H
K
s
bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limited to 9-band detections, based on a feature space built from magnitudes and their combinations. We show that projections of the high-dimensional feature space on two dimensions can be successfully used, instead of the standard color-color plots, to investigate the photometric estimations, compare them with spectroscopic data, and efficiently support the process of building a catalog. The model selection and fine-tuning employs two subsets of objects: those randomly selected and the faintest ones, which allowed us to properly fit the bias versus variance trade-off. We tested three ML models: random forest (RF), XGBoost (XGB), and artificial neural network (ANN). We find that XGB is the most robust and straightforward model for classification, while ANN performs the best for combined classification and redshift. The ANN inference results are tested using number counts,
Gaia
parallaxes, and other quasar catalogs that are external to the training set. Based on these tests, we derived the minimum classification probability for quasar candidates which provides the best purity versus completeness trade-off:
p
(QSO
cand
) > 0.9 for
r
< 22 and
p
(QSO
cand
) > 0.98 for 22 <
r
< 23.5. We find 158 000 quasar candidates in the safe inference subset (
r
< 22) and an additional 185 000 candidates in the reliable extrapolation regime (22 <
r
< 23.5). Test-data purity equals 97% and completeness is 94%; the latter drops by 3% in the extrapolation to data fainter by one magnitude than the training set. The photometric redshifts were derived with ANN and modeled with Gaussian uncertainties. The test-data redshift error (mean and scatter) equals 0.009 ± 0.12 in the safe subset and −0.0004 ± 0.19 in the extrapolation, averaged over a redshift range of 0.14 <
z
< 3.63 (first and 99th percentiles). Our success of the extrapolation challenges the way that models are optimized and applied at the faint data end. The resulting catalog is ready for cosmology and active galactic nucleus (AGN) studies.
The LOFAR Two-metre Sky Survey Shimwell, T. W.; Hardcastle, M. J.; Tasse, C. ...
Astronomy and astrophysics (Berlin),
03/2022, Letnik:
659
Journal Article
Recenzirano
Odprti dostop
In this data release from the ongoing LOw-Frequency ARray (LOFAR) Two-metre Sky Survey we present 120–168 MHz images covering 27% of the northern sky. Our coverage is split into two regions centred ...at approximately 12h45m +44°30′ and 1h00m +28°00′ and spanning 4178 and 1457 square degrees respectively. The images were derived from 3451 h (7.6 PB) of LOFAR High Band Antenna data which were corrected for the direction-independent instrumental properties as well as direction-dependent ionospheric distortions during extensive, but fully automated, data processing. A catalogue of 4 396 228 radio sources is derived from our total intensity (Stokes
I
) maps, where the majority of these have never been detected at radio wavelengths before. At 6″ resolution, our full bandwidth Stokes
I
continuum maps with a central frequency of 144 MHz have: a median rms sensitivity of 83 μJy beam
−1
; a flux density scale accuracy of approximately 10%; an astrometric accuracy of 0.2″; and we estimate the point-source completeness to be 90% at a peak brightness of 0.8 mJy beam
−1
. By creating three 16 MHz bandwidth images across the band we are able to measure the in-band spectral index of many sources, albeit with an error on the derived spectral index of > ± 0.2 which is a consequence of our flux-density scale accuracy and small fractional bandwidth. Our circular polarisation (Stokes
V
) 20″ resolution 120–168 MHz continuum images have a median rms sensitivity of 95 μJy beam
−1
, and we estimate a Stokes
I
to Stokes
V
leakage of 0.056%. Our linear polarisation (Stokes
Q
and Stokes
U
) image cubes consist of 480 × 97.6 kHz wide planes and have a median rms sensitivity per plane of 10.8 mJy beam
−1
at 4′ and 2.2 mJy beam
−1
at 20″; we estimate the Stokes
I
to Stokes
Q
/
U
leakage to be approximately 0.2%. Here we characterise and publicly release our Stokes
I
,
Q
,
U
and
V
images in addition to the calibrated
uv
-data to facilitate the thorough scientific exploitation of this unique dataset.
ABSTRACT
Covering $\sim 5600\, \deg ^2$ to rms sensitivities of ∼70−100 $\mu$Jy beam−1, the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS-DR2) provides the largest low-frequency (∼150 MHz) radio ...catalogue to date, making it an excellent tool for large-area radio cosmology studies. In this work, we use LoTSS-DR2 sources to investigate the angular two-point correlation function of galaxies within the survey. We discuss systematics in the data and an improved methodology for generating random catalogues, compared to that used for LoTSS-DR1, before presenting the angular clustering for ∼900 000 sources ≥1.5 mJy and a peak signal-to-noise ≥ 7.5 across ∼80 per cent of the observed area. Using the clustering, we infer the bias assuming two evolutionary models. When fitting angular scales of $0.5 \le \theta \lt 5{^\circ }$, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of $b_{\rm C}= 2.14^{+0.22}_{-0.20}$ (assuming constant bias) and $b_{\rm E}(z=0)= 1.79^{+0.15}_{-0.14}$ (for an evolving model, inversely proportional to the growth factor), corresponding to $b_{\rm E}= 2.81^{+0.24}_{-0.22}$ at the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces to $b_{\rm C}= 2.02^{+0.17}_{-0.16}$ and $b_{\rm E}(z=0)= 1.67^{+0.12}_{-0.12}$ when allowing preferential redshift distributions from the Deep Fields to model our data. Whilst the clustering amplitude is slightly lower than LoTSS-DR1 (≥2 mJy), our study benefits from larger samples and improved redshift estimates.
We present a bright galaxy sample with accurate and precise photometric redshifts (photo-zs), selected using ugriZYJHKs photometry from the Kilo-Degree Survey (KiDS) Data Release 4. The highly pure ...and complete dataset is flux-limited at r < 20 mag, covers ∼1000 deg2, and contains about 1 million galaxies after artifact masking. We exploit the overlap with Galaxy And Mass Assembly spectroscopy as calibration to determine photo-zs with the supervised machine learning neural network algorithm implemented in the ANNz2 software. The photo-zs have a mean error of |⟨δz⟩|∼5 × 10−4 and low scatter (scaled mean absolute deviation of ∼0.018(1 + z)); they are both practically independent of the r-band magnitude and photo-z at 0.05 < zphot < 0.5. Combined with the 9-band photometry, these allow us to estimate robust absolute magnitudes and stellar masses for the full sample. As a demonstration of the usefulness of these data, we split the dataset into red and blue galaxies, used them as lenses, and measured the weak gravitational lensing signal around them for five stellar mass bins. We fit a halo model to these high-precision measurements to constrain the stellar-mass–halo-mass relations for blue and red galaxies. We find that for high stellar mass (M⋆ > 5 × 1011 M⊙), the red galaxies occupy dark matter halos that are much more massive than those occupied by blue galaxies with the same stellar mass.
We present a bright galaxy sample with accurate and precise photometric redshifts (photo-
z
s), selected using
ugriZYJHK
s
photometry from the Kilo-Degree Survey (KiDS) Data Release 4. The highly ...pure and complete dataset is flux-limited at
r
< 20 mag, covers ∼1000 deg
2
, and contains about 1 million galaxies after artifact masking. We exploit the overlap with Galaxy And Mass Assembly spectroscopy as calibration to determine photo-
z
s with the supervised machine learning neural network algorithm implemented in the ANNz2 software. The photo-
z
s have a mean error of |⟨
δz
⟩|∼5 × 10
−4
and low scatter (scaled mean absolute deviation of ∼0.018(1 +
z
)); they are both practically independent of the
r
-band magnitude and photo-
z
at 0.05 <
z
phot
< 0.5. Combined with the 9-band photometry, these allow us to estimate robust absolute magnitudes and stellar masses for the full sample. As a demonstration of the usefulness of these data, we split the dataset into red and blue galaxies, used them as lenses, and measured the weak gravitational lensing signal around them for five stellar mass bins. We fit a halo model to these high-precision measurements to constrain the stellar-mass–halo-mass relations for blue and red galaxies. We find that for high stellar mass (
M
⋆
> 5 × 10
11
M
⊙
), the red galaxies occupy dark matter halos that are much more massive than those occupied by blue galaxies with the same stellar mass.
Aims
. We combined the LOw-Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS) second data release (DR2) catalogue with gravitational lensing maps from the cosmic microwave background (CMB) to place ...constraints on the bias evolution of LoTSS-detected radio galaxies, and on the amplitude of matter perturbations.
Methods
. We constructed a flux-limited catalogue from LoTSS DR2, and analysed its harmonic-space cross-correlation with CMB lensing maps from
Planck
,
C
ℓ
gk
, as well as its auto-correlation,
C
ℓ
gg
. We explored the models describing the redshift evolution of the large-scale radio galaxy bias, discriminating between them through the combination of both
C
ℓ
gk
and
C
ℓ
gg
. Fixing the bias evolution, we then used these data to place constraints on the amplitude of large-scale density fluctuations, parametrised by
σ
8
.
Results
. We report the significance of the
C
ℓ
gk
signal at a level of 26.6
σ
. We determined that a linear bias evolution of the form
b
g
(
z
) =
b
g,D
/D(
z
), where
D
(
z
) is the growth rate, is able to provide a good description of the data, and we measured
b
g,D
= 1.41 ± 0.06 for a sample that is flux limited at 1.5 mJy, for scales
ℓ
< 250 for
C
ℓ
gg
, and
ℓ
< 500 for
C
ℓ
gk
. At the sample’s median redshift, we obtained
b
(
z
= 0.82) = 2.34 ± 0.10. Using
σ
8
as a free parameter, while keeping other cosmological parameters fixed to the
Planck
values, we found fluctuations of σ
8
= 0.75
−0.04
+0.05
. The result is in agreement with weak lensing surveys, and at 1
σ
difference with
Planck
CMB constraints. We also attempted to detect the late-time-integrated Sachs-Wolfe effect with LOFAR data; however, with the current sky coverage, the cross-correlation with CMB temperature maps is consistent with zero. Our results are an important step towards constraining cosmology with radio continuum surveys from LOFAR and other future large radio surveys.
Abstract Optical surveys have become increasingly adept at identifying candidate tidal disruption events (TDEs) in large numbers, but classifying these generally requires extensive spectroscopic ...resources. Here we present tdescore , a simple binary photometric classifier that is trained using a systematic census of ∼3000 nuclear transients from the Zwicky Transient Facility (ZTF). The sample is highly imbalanced, with TDEs representing ∼2% of the total. tdescore is nonetheless able to reject non-TDEs with 99.6% accuracy, yielding a sample of probable TDEs with recall of 77.5% for a precision of 80.2%. tdescore is thus substantially better than any available TDE photometric classifier scheme in the literature, with performance not far from spectroscopy as a method for classifying ZTF nuclear transients, despite relying solely on ZTF data and multiwavelength catalog cross matching. In a novel extension, we use “Shapley additive explanations” to provide a human-readable justification for each individual tdescore classification, enabling users to understand and form opinions about the underlying classifier reasoning. tdescore can serve as a model for photometric identification of TDEs with time-domain surveys, such as the upcoming Rubin observatory.
We combine the LOw-Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS) second data release (DR2) catalogue with gravitational lensing maps from the Cosmic Microwave Background (CMB) to place ...constraints on the bias evolution of LoTSS radio galaxies, and on the amplitude of matter perturbations. We construct a flux-limited catalogue, and analyse its harmonic-space cross-correlation with CMB lensing maps from Planck, \(C_\ell^{g\kappa}\), as well as its auto-correlation, \(C_\ell^{gg}\). We explore the models describing the redshift evolution of the large-scale radio galaxy bias, discriminating between them through the combination of both \(C_\ell^{g\kappa}\) and \(C_\ell^{gg}\). Fixing the bias evolution, we then use these data to place constraints on the amplitude of large scale density fluctuations. We report the significance of the \(C_\ell^{g\kappa}\) signal at a level of \(26.6\sigma\). We determine that a linear bias evolution of the form \(b_g(z) = b_{g,D} / D(z)\), where \(D(z)\) is the growth rate, is able to provide a good description of the data, and measure \(b_{g,D} = 1.41 \pm 0.06\) for a sample flux-limited at \(1.5\,{\rm mJy}\), for scales \(\ell < 250\) for \(C_\ell^{gg}\), and \(\ell < 500\) for \(C_\ell^{g\kappa}\). At the sample's median redshift, we obtain \(b(z = 0.82) = 2.34 \pm 0.10\). Using \(\sigma_8\) as a free parameter, while keeping other cosmological parameters fixed to the Planck values, we find fluctuations of \(\sigma_8 = 0.75^{+0.05}_{-0.04}\). The result is in agreement with weak lensing surveys, and at \(1\sigma\) difference with Planck CMB constraints. We also attempt to detect the late-time integrated Sachs-Wolfe effect with LOFAR, but with the current sky coverage, the cross-correlation with CMB temperature maps is consistent with zero. Our results are an important step towards constraining cosmology with radio continuum surveys from LOFAR and other future large radio surveys.
Covering \(\sim\)5600 deg\(^2\) to rms sensitivities of \(\sim\)70\(-\)100 \(\mu\)Jy beam\(^{-1}\), the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS-DR2) provides the largest low-frequency ...(\(\sim\)150 MHz) radio catalogue to date, making it an excellent tool for large-area radio cosmology studies. In this work, we use LoTSS-DR2 sources to investigate the angular two-point correlation function of galaxies within the survey. We discuss systematics in the data and an improved methodology for generating random catalogues, compared to that used for LoTSS-DR1, before presenting the angular clustering for \(\sim\)900,000 sources $\geq$$1.5\( mJy and a peak signal-to-noise \)\geq$$7.5\( across \)\sim$$80\%\( of the observed area. Using the clustering we infer the bias assuming two evolutionary models. When fitting {angular scales of \)0.5 \leq\theta<5\,\deg\(, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of \)b_{C}= 2.14^{+0.22}_{-0.20}\( (assuming constant bias) and \)b_{E}(z=0)= 1.79^{+0.15}_{-0.14}\( (for an evolving model, inversely proportional to the growth factor), corresponding to \)b_E= 2.81^{+0.24}_{-0.22}\( at the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces to \)b_{C}= 2.02^{+0.17}_{-0.16}\( and \)b_{E}(z=0)= 1.67^{+0.12}_{-0.12}\( when allowing preferential redshift distributions from the Deep Fields to model our data. Whilst the clustering amplitude is slightly lower than LoTSS-DR1 (\)\geq$2 mJy), our study benefits from larger samples and improved redshift estimates.
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